Surface distribution of crackling sounds

Boundary element model for simulating sound propagation and source localization within the lungs

“…[7][8][9][10] Indeed, simultaneous, multisensor auscultation methods have been developed to "map" sounds on the thoracic surface by several groups. 9,[11][12][13][14] Beyond this mapping process, Kompis et al 10 attempted to form a three-dimensional ͑3D͒ acoustic image of the likely sound source͑s͒ location͑s͒ by using multiple sensors and assuming "ray acoustic," i.e., "free field," models for how sound propagated away from these sources. In their study, they noted that a useful imaging system for the human lung should: ͑1͒ be robust with respect to acoustic properties, especially speed of sound which varies and is not precisely known; ͑2͒ provide 3D data sets and resulting images that are intuitively interpretable; and ͑3͒ be robust with respect to missing sensors or noisy data in individual sensors.…”

“…In recent years, many researchers have applied more quantitative measurement and analysis techniques to increase the diagnostic utility of this approach, utilizing electronic sensors and applying computational signal processing and statistical analyses to the measured signals to discern trends or biases correlated with pathologies. [2][3][4][5][6][7][8][9][10][11][12][13][14] To reap the full potential of the inherently rich source of diagnostic information within the audible frequency regime will require a better fundamental understanding of: ͑1͒ the acoustic source and its relation to pathology, ͑2͒ the acoustic path from the source to the sensor, which can be far more complex at sonic than ultrasonic frequencies due to the potential for multiple reflections, multiple propagating wave types, and multipath behavior, and ͑3͒ the use of more accurate and multiple measurement sensors. ͑4͒ It could also require more sophisticated and spatially resolved computational processing of the measured signals that considers multipath propagation of the acoustic event from its source to the sensor location to reconstruct a sonic image ingrained with quantitative information.…”

Acoustic Imaging of the Human Chest

“…18 In addition, the algorithm should be able to generate a spatial representation of intrathoracic sounds, as opposed to the mapping of sounds on the thoracic surface. [7][8][9] A Robust Acoustic Imaging Algorithm Based on the above-mentioned goals, an acoustic imaging algorithm was developed. The algorithm consists of two parts: the calculation of a threedimensional data array, and the graphic representation of this array.…”

“…4 Thoracic sounds are known to contain spatial information that can be accurately accessed using simultaneous multimicrophone recordings but not by successive auscultation at different locations of the thoracic surface. 5,6 The use of this additional spatial information may lead to acoustic imaging methods beyond the relatively simple mapping of sounds on the thoracic surface, which has been proposed both for lung 7,8 and heart sounds. 9 In this study, a novel acoustic imaging method for the human respiratory system that exploits this additional spatial information is proposed and evaluated.…”

A comprehensive computational model of sound transmission through the porcine lung

“…[3][4][5][6] Indeed simultaneous, multi-sensor auscultation methods have been developed to "map" sounds on the thoracic surface by several groups. 5,[7][8][9][10][11] Also recently the phase contrast-based technique known as magnetic resonance elastography (MRE) has been applied to the lungs in pilot studies with limited success. [12][13][14][15] MRE seeks to provide a map of the viscoelastic properties within the region of interest that will affect the shear wave motion that MRE measures.…”